1. Τι είναι μια ψευδαίσθηση AI;​

Οι ψευδαισθήσεις AI συμβαίνουν όταν ένας συνομιλητικός πράκτορας, όπως ένα chatbot, παράγει μια λανθασμένη, ασύνδετη ή εντελώς κατασκευασμένη απάντηση. Αυτά τα σφάλματα δεν οφείλονται σε τεχνικό σφάλμα, αλλά στον τρόπο που τα γλωσσικά μοντέλα επεξεργάζονται τα δεδομένα. Σε περίπτωση που δεν υπάρχει σχετική πληροφορία στη βάση δεδομένων του, η AI μπορεί να προσπαθήσει να "μαντέψει" μια πειστική απάντηση, ακόμη και αν είναι λανθασμένη.

Tokens are fundamental elements to understand how large language models (LLMs) work. If you have ever used a tool based on an LLM, such as a chatbot or a voice assistant, it is likely that these tools process your requests by breaking them down into "tokens." But what exactly is a token, and why is it essential?

In this article, we will delve deep into the world of AI agents, exploring their foundations, their architecture, and the various building blocks that compose them. We will also look at how they can be integrated into different fields, the benefits they bring, and why these technologies are attracting growing interest in businesses and among the general public.

Introduction​

In recent years, artificial intelligence (AI) has gained increasing popularity, fueled notably by the democratization of powerful natural language processing (NLP) models and large language models (LLMs). Nowadays, these technologies go beyond mere text generation or auto-completion: they give rise to more complex, more autonomous systems capable of acting and interacting on behalf of the user. These systems—commonly referred to as AI agents—are designed to handle all sorts of tasks, from simply answering frequent questions to managing an entire complex process.

Imagine a field of wildflowers stretching as far as the eye can see, where an oversized swarm of bees is busily buzzing around. They flutter, gather pollen from every bloom, and turn it into incredibly complex honey. That honey is language. And these bees are the LLMs (Large Language Models), those giant language models that work tirelessly to transform vast amounts of textual data into something structured, coherent, and sometimes even highly creative.

If language were a symphony, its score would be infinitely complex—sometimes grand, sometimes intimate—driven by the diversity of languages, contexts, and cultural nuances. At the heart of this symphony lies a subtle yet crucial orchestra: NLP (Natural Language Processing), which orchestrates words and meaning in the world of AI.

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